We train GMMC on three benchmark datasets: CIFAR10, CIFAR100 [1]} and SVHN [2]}, and compare it to the state-of-the-art hybrid models, as well as standalone generative and discriminative models. Following the settings of JEM, we use the Wide-ResNet [3]} as the backbone CNN model for JEM and GMMC. To evaluate the quality of generated images, we adopt Inception Score (IS) [4]} and Fréchet Inception Distance (FID) [5]} as the evaluation metrics.
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